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020 ▼a 9780438338753
035 ▼a (MiAaPQ)AAI10931980
035 ▼a (MiAaPQ)cmu:10290
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 629.8
1001 ▼a Rodrigues, Jose Jeronimo Moreira.
24510 ▼a 3D Pose Estimation for Bin-picking: A Data-driven Approach Using Multi-light Images.
260 ▼a [S.l.] : ▼b Carnegie Mellon University., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 113 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
500 ▼a Includes supplementary digital materials.
500 ▼a Advisers: Takeo Kanade
5021 ▼a Thesis (Ph.D.)--Carnegie Mellon University, 2018.
520 ▼a We study the problem of 3D pose estimation of textureless shiny objects from monocular 2D images, for a bin-picking task. The main challenge of dealing with a shiny object comes from the fact that the object appearance largely changes with its p
520 ▼a In this thesis, we develop a purely data-driven method to tackle the pose estimation problem. Motivated by photometric stereo, we develop an imaging system with multiple lights to acquire a multi-light image where channels are obtained by varyin
520 ▼a Experiments show that the given method can detect and estimate poses of textureless and shiny objects accurately and robustly within half a second. We further compare our approach with the HALCON commercial software, a highly optimized hierarchi
590 ▼a School code: 0041.
650 4 ▼a Robotics.
650 4 ▼a Computer science.
650 4 ▼a Computer engineering.
690 ▼a 0771
690 ▼a 0984
690 ▼a 0464
71020 ▼a Carnegie Mellon University. ▼b Electrical and Computer Engineering.
7730 ▼t Dissertation Abstracts International ▼g 80-01B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0041
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15001069 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자